应用系统工程方法确定邯郸市人民路立交桥最优施工方案

邯郸市人民路立交桥位于京广铁路与人民路交叉处,主体箱涵长66.5米,宽30.4米,总重量达1166吨,横穿十一股铁路线,全顶程71.23米,主体箱涵的长度、孔径和穿越铁路的股道数居全国之首.该工程是邯郸市重点工程之一,总投资1200万元.市政府规定工期为16个月.我们应用了系统工程方法,对该工程施工方案的选择设计、施工计划的组织实施进行了整体优化. 一、系统分析,工程设计方案的优化 在大型公路与铁路立交桥的建造中,主体箱涵施工方法的选择直接影响着整个工程的工期、费用和安全,如何寻求一个最优的箱涵顶进施工方法是本工程所要解决的关键问题,…     

施工网络计划优化的极值种群遗传算法

针对普通遗传算法用于施工网络计划优化的缺点,通过种群划分与极值搜索,建立了网络计划优化的极值种群改进遗传算法模型,有效地避免了陷入局部极值点,应用证明,该算法与普通遗传算法相比,具有优化速度快、求解精度高,全局寻优能力强等优点,尤其适合于大型复杂工程网络的优化计算。     

基于灰色关联的网络计划综合优化

针对建设项目追求质量最优、工期最短、费用最低、资源使用最均衡并体现出安全施工和工程风险信息的目标,从灰色关联的基本原理出发,通过计算网络计划中各可行方案与虚拟最优方案的安全、质量、费用、工期集成的灰色关联度,得出方案的优劣排序,对工程项目管理具有实际的应用价值.     

区间数型地铁绿色施工方案优化模型及其应用

地铁绿色施工方案优化时由于各专家对待优化方案的意见不同,其评价指标多以区间数形式表示.针对待优化地铁绿色施工方案不能直接比较优劣的问题,根据区间数的误差分布形式将区间数转化为a+bi型联系数,按优化方案要求构造"理想方案"和"负理想方案",采用主、客观组合赋权法计算各方案与"理想方案"和"负理想方案"的加权海明距离,运用扩展的最小二乘方准则构造目标函数,建立了区间数型地铁绿色施工方案优化模型.通过一地铁4种绿色施工方案优化实例进行了计算分析,得到优化的绿色施工方案.计算分析结果表明,模型计算简便,赋权合理,优化方案更接近工程实际.     

工程网络计划时间——费用分析的模糊规划

初始的网络计划不一定是最优的,甚至不是一个可行的网络计划,在时间或成本等方面可能存在着一些矛盾和不足,必须通过网络计划的优化方法来加以完善与解决。目前较常用的网络计划优化方法是参数线性规划,它综合地考虑了时间,费用等因素。但使用这种方法时,必须准确地知道工作最短延续时间,工作正常延续时间,总工期及有关费用等,而在实际工程中,由于各种因素影响(人员的变动,成本的波动等,)特别是面临一项新的工程时,往往无法确切地定出模型中参数所需要的量值,只能给出参数量值大致可能的范围,这就需要将一般的参数线性规划拓展为模糊规划。本文在参数线性规划的基础上对工程网络计划时间——费用分析实行模糊规划,并在计算机上调试运行成功,取得了较满意的效果。计算的结果表明,工程网络时间——费用分析模糊规划的优化结果使计划者获得了更充分的决策余地。     

基于未确知有理数的施工网络研究

提出未确知有理数用于施工网络计划,介绍未确知有理数概念、运算、未确知期望.建立未确知施工网络计划,提出未确知施工网络计划关键线路计算模型,确定关键线路和未确知施工工期.讨论不确定性网络计划的研究.     

从一个编制计划的案例说网络计划法

网络计划法是以网络图反映、表达计划安排,据以选择最优工作方案,组织协调和控制生产(项目)的进度(时间)和费用(成本),使其达到预定目标,获得更佳经济效益的一种优化决策方法.     

现行审计计划方法的优化：网络计划技术在审计计划中的运用分析

文章提出了将网络计划技术运用于审计计划的编制进而优化现行审计计划方法的思路,并对这一优化过程的条件、步骤进行了综合分析     

CIMS项目网络计划技术中成本优化算法研究

现有的网络计划在描述项目时已不能适应越来越大型和复杂的C IM S项目,为此,对现有网络计划中任务的约束条件及逻辑关系进行了扩充,并给出了扩充网络计划中时间参数的计算.在此基础上,提出了一种基于样本的成本优化算法,有效地解决了实际项目中的成本优化问题.     

土木工程投标报价模型研究(英文)

本文主要研究单一不可分土木工程的n人投标报价模型.报价高低不是是否中标的唯一决定性因素,施工方案和工程报价为赢得工程施工合同共同发挥组合效应,并且在一定条件下,通过工程竟标,中标价会趋于Nash平衡.     

Evolutionary Pareto optimizers for continuous review stochastic inventory systems

Multi-objective inventory control has been studied for a long time. The trade-off analysis of cycle stock investment and workload, so called the exchange curve concept, possibly dates back to several decades ago. A classical way to such trade-off analysis is to utilize the Lagrangian relaxation technique or interactive method to search for the optimum in a sequence of single objective optimization problems. However, the field of optimization has been changed over the last few decades since the concept of evolutionary computation was introduced. In this paper, a continuous review stochastic inventory system with three objectives about cost and shortage is resolved by evolutionary computation in order to plan for the control policies under backordering and lost sales. Two evolutionary optimizers, multi-objective electromagnetism-like optimization (MOEMO) and multi-objective particle swarm optimization (MOPSO), are employed to well and fast approximate the non-dominated policies in term of lot size and safety stock. Trade-offs are observed in a non-dominated set that no one excels the others in all objectives. Computational results show that the evolutionary Pareto optimizers could generate trade-off solutions potentially ignored by the well-known simultaneous method. Comparisons between the results of backordering and lost sales indicate that decision makers will make more deliberate choices about lot sizing and safety stocking when unsatisfied demand is completely lost.     

Branch and bound based solution algorithms for the budget constrained discrete time/cost trade-off problem

The time/cost trade-off models in project management aim to reduce the project completion time by putting extra resources on activity durations. The budget problem in discrete time/cost trade-off scheduling selects a time/cost mode for each activity so as to minimize the project completion time without exceeding the available budget. There may be alternative modes that solve the budget problem optimally and each solution may have a different total cost value. In this study we consider the budget problem and aim to find the minimum cost solution among the minimum project completion time solutions. We analyse the structure of the problem together with its linear programming relaxation and derive some mechanisms for reducing the problem size. We solve the reduced problem by branch and bound based optimization and heuristic algorithms. We find that our branch and bound algorithm finds optimal solutions for medium-sized problem instances in reasonable times and the heuristic algorithms produce high quality solutions very quickly.     

不确定条件下工程项目的多目标模糊均衡优化

在工程项目多目标优化问题研究基础上,研究不确定环境下工程项目多目标均衡优化问题.利用模糊数表示费用变化率和质量变化率,考虑模糊集的不同可能性水平,建立工程项目多目标模糊均衡优化模型,给出模型的求解方法和步骤,得到不同可能性水平下多目标优化问题的最优折衷解变化范围.优化方法使决策者能够根据决策风险的大小进行最优目标值的确定.     

A robust optimization model for multi-site production planning problem in an uncertain environment

This paper addresses the multi-site production planning problem for a multinational lingerie company in Hong Kong subject to production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers’ preferences, as well as production capacity, workforce level, storage space and resource conditions at the factories. In this paper, a robust optimization model is developed to solve multi-site production planning problem with uncertainty data, in which the total costs consisting of production cost, labor cost, inventory cost, and workforce changing cost are minimized. By adjusting penalty parameters, production management can determine an optimal medium-term production strategy including the production loading plan and workforce level while considering different economic growth scenarios. The robustness and effectiveness of the developed model are demonstrated by numerical results. The trade-off between solution robustness and model robustness is also analyzed.     

军事设施建设项目管理综合集成研究

工程建设项目是军事设施建设的重要组分, 对我军建设发展具有深远影响。本文以我军军事设施建设项目管理集成为研究对象, 综合考虑项目成本、进度、质量和安全等参与要素的动态影响关系, 对项目生命周期全过程, 即规划统筹阶段、计划统控阶段、勘察设计阶段、施工建设阶段和跟踪管理阶段进行综合集成管理, 并提出当前可应用于军事设施建设项目综合集成管理的主要方法, 对军事建设项目管理过程进行了优化。     

Time-cost trade-off analysis of project networks in fuzzy environments

This paper proposes a novel approach for time-cost trade-off analysis of a project network in fuzzy environments. Different from the results of previous studies, in this paper the membership function of the fuzzy minimum total crash cost is constructed based on Zadeh’s extension principle and fuzzy solutions are provided. A pair of two-level mathematical programs parameterized by possibility level α is formulated to calculate the lower and upper bounds of the fuzzy minimum total crash cost at α. By enumerating different values of α, the membership function of the fuzzy minimum total crash cost is constructed, and the corresponding optimal activity time for each activity is also obtained at the same time. An example of time-cost trade-off problem with several fuzzy parameters is solved successfully to demonstrate the validity of the proposed approach. Since the minimum total crash cost is expressed by a membership function rather than by a crisp value, the fuzziness of parameters is conserved completely, and more information is provided for time-cost trade-off analysis in project management. The proposed approach also can be applied to time-cost trade-off problems with other characteristics.     

不确定环境下基于时间、费用及鲁棒性权衡的多目标项目调度优化

项目调度中的时间和费用是两个重要的指标,而在不确定环境下进度计划的鲁棒性则是保证项目平稳实施的关键。本文研究不确定环境下的多目标项目调度优化问题,以优化项目的工期、鲁棒值和成本为目标安排各活动的开始时间。基于此,作者构建多目标项目调度优化模型,将模型分解为三个子模型分析目标间的权衡关系,然后设计非劣排序遗传算法进行求解,应用精英保留策略和基于子模型权衡关系的优化策略优化算法,进行算法测试和算例参数敏感性分析。最后,应用上述方法研究一个项目实例,计算得到非劣解集,实例的敏感性分析结果进一步验证了三个目标间的权衡关系,据此提出资源的有效利用策略。本文的研究可以为多目标项目调度制定进度计划提供定量化决策支持。     

A modified active set algorithm for transportation discrete network design bi-level problem

Transportation discrete network design problem (DNDP) is about how to modify an existing network of roads and highways in order to improve its total system travel time, and the candidate road building or expansion plan can only be added as a whole. DNDP can be formulated into a bi-level problem with binary variables. An active set algorithm has been proposed to solve the bi-level discrete network design problem, while it made an assumption that the capacity increase and construction cost of each road are based on the number of lanes. This paper considers a more general case when the capacity increase and construction cost are specified for each candidate plan. This paper also uses numerical methods instead of solvers to solve each step, so it provides a more direct understanding and control of the algorithm and running procedure. By analyzing the differences and getting corresponding solving methods, a modified active set algorithm is proposed in the paper. In the implementation of the algorithm and the validation, we use binary numeral system and ternary numeral system to avoid too many layers of loop and save storage space. Numerical experiments show the correctness and efficiency of the proposed modified active set algorithm.     

Cost impact of float loss on a project with adjustable activity durations

Although delays to non-critical activities within the float do not always affect the overall completion time of a project, they commonly cause disputes over the impact cost and apportionment resulting from the complexity of resource utilization in construction projects. Therefore, considerable attention has been focused on providing an effective and reliable method for analysing the effects of float loss. Several recent studies have proposed various methods; however, most of these methods are based on the assumption of a fixed duration for each activity or activity-based cost simulation. Few studies have considered the trade-off between time and costs and the integration of project resources. Using genetic algorithms, this study introduces a critical path method (CPM)-modified resource-integrated optimization model and successfully quantifies the impact of float loss on the total cost of the project. The results provide objective quantification for accurately evaluating the impact of within-float delays and facilitate the analysis of the impact of delay claims on cost and apportionment in construction projects.